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Artificial Intelligence Deployment Center of Excellence (AI COE)

rosaP Repository & Open Science Access Portal

The AI COE Collection is a central resource for transportation stakeholders that may aid in deployment of safe and responsible AI in surface transportation. The collection will feature current and emerging resources, innovations, and technologies. For more information on the AI COE, go to https://highways.dot.gov/ai-coe.

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Showing 481 - 500 of 613 results
  • Work Zone Safety III Calibration of Safety Notifications through Reinforcement Learning and Eye Tracking
    Work Zone Safety III: Calibration of Safety Notifications through Reinforcement Learning and Eye Tracking
    Ergan, Semiha ;
    Ozbay, Kaan
    2022-05-01 | PDF
    Despite increased regulations, restrictive measures, and devices used for warnings, work zone injuries and fatalities are still observed at highway construction projects with alarms/notifications being ignored. With a vision to reduce the number of injuries and fatalities, Phase 3 of the research team's worker safety project extends the original sc ...
  • RealTime Traffic Signal System Performance Measurement Phase II Data and Functionality Enhancement Large Scale Deployment Connected and Autonomous Vehicles Integration
    Real-Time Traffic Signal System Performance Measurement Phase II: Data and Functionality Enhancement, Large Scale Deployment, Connected and Autonomous Vehicles Integration
    Jin, Peter J. ;
    Zhang, Tianya
    2022-05-01 | PDF
    Traffic signal performance measurement and visualization provide insights as operational tools to help traffic management centers (TMC) get more paybacks from infrastructure investment. However, evaluating and monitoring signal performance is challenging in real-time, which requires immediate data collection and analysis capability. As part of the ...
  • Driving Risk Assessment Based on Highfrequency Highresolution Telematics Data
    Driving Risk Assessment Based on High-frequency, High-resolution Telematics Data
    Guo, Feng ;
    Qian, Chen
    2022-04-01 | PDF
    The emerging connected vehicle and Automated Driving System (ADS), the widely available advanced in-vehicle telematics data collection/transmitting systems, as well as smartphone apps produce gigantic amount of high-frequency, high-resolution driving data. These telematics data provide comprehensive information on driving style, driving environment ...
  • Development of a Geometric Extraction Framework as Part of a Pilot Digital Twin Framework for OpenDeck Rail Bridges
    Development of a Geometric Extraction Framework as Part of a Pilot Digital Twin Framework for Open-Deck Rail Bridges
    Najafi, Amirali
    ORCID ICON IMG
    2022-04-01 | PDF
    Open-deck railway bridges require expensive and customized timber sleepers. When these sleepers are due for replacement, a manual process for geometry measurement is necessary which can be time consuming, inaccurate, and expensive. In addition, significant downtime is required for the safety of the inspectors that measure and assess the conditions ...
  • A Realtime Proactive Intersection Safety Monitoring System Based on Video Data
    A Real-time Proactive Intersection Safety Monitoring System Based on Video Data
    Jalayer, Mohammad ;
    Bouaynaya, Nidhal Carla
    2022-04-01 | PDF
    In recent years, identifying road users' behavior and conflicts at intersections have become an essential data source for evaluating traffic safety. According to the Federal Highway Administration (FHWA), in 2020, more than 50% of fatal and injury crashes occurred at or near the intersections, necessitating further investigation. This study develop ...
  • Micromobility as a Solution To Reduce Urban Traffic Congestion
    Micromobility as a Solution To Reduce Urban Traffic Congestion
    Zhao, Xilei ;
    Sisiopiku, Virginia P.
    2022-03-29 | PDF
    Micromobility is an innovative transportation strategy that has demonstrated a great potential for congestion mitigation. However, the research on micromobility is very limited in the field of transportation. This project aims to conduct a comprehensive study to analyze, quantify, and understand the impacts of micromobility on congestion reduction ...
  • Developing an Intelligent Connected Vehicle Based Traffic State Estimator
    Developing an Intelligent Connected Vehicle Based Traffic State Estimator
    Aljamal, Mohammad A ;
    Farag, Mohamed
    2022-03-01 | PDF
    Estimation of traffic state parameters is crucial in advanced traffic management systems. However, measuring these parameters in the field is not practical since they are categorized as spatiotemporal parameters. This report presents three estimation approaches to estimate the traffic volume existing on signalized links. The first approach includes ...
  • Artificial IntelligenceAided Rail Transit Infrastructure Data Mining
    Artificial Intelligence-Aided Rail Transit Infrastructure Data Mining
    Liu, Xiang ;
    Dai, Junyan
    2022-03-01 | PDF
    Signals are an important part of the urban rail transit system. Signals being in functioning condition is key to rail transit safety. Predicting rail transit signal failures ahead of time has significant benefits with regard to operating safety and efficiency. This paper proposes a machine learning method for predicting urban rail transit signal fa ...
  • RealTime Network Assessment and Updating Using VehicleLocating Data
    Real-Time Network Assessment and Updating Using Vehicle-Locating Data
    Tien, Iris ;
    Roberts, Zachary
    2022-03-01 | PDF
    This project explores the ability to use vehicle-locating data to assess the state of the road network, including identifying road blockages along different segments of the transportation system. The project utilizes the mobile sources of Georgia Department of Transportation (GDOT) vehicles and their associated vehicle-tracking information to infer ...
  • A Review of Floridas FC5 Raveling Condition Assessment and Measurement Methods
    A Review of Florida's FC-5 Raveling Condition Assessment and Measurement Methods
    Tsai, Yichang (James) ;
    Hsieh, Yung-An
    2022-02-28 | PDF
    While open-graded friction course (OGFC) mixtures, called FC-5 in the Florida Department of Transportation (FDOT), provide several safety benefits, their lives are limited to approximately 14 years on average in Florida. The reduced life is generally due to raveling, which rapidly deteriorates once initiated. In FDOT, raveling is rolled up into the ...
  • Improving Security and User Privacy in LearningBased Traffic Signal Controllers TSC
    Improving Security and User Privacy in Learning-Based Traffic Signal Controllers (TSC)
    Chuah, Chen-Nee
    ORCID ICON IMG
    2022-02-28 | PDF
    The 21st century of transportation systems leverages intelligent learning agents and data-centric approaches to analyze information gathered with sensing (both vehicles and roadsides) or shared by users to improve transportation efficiency and safety. Numerous machine learning (ML) models have been incorporated to make control decisions (e.g., traf ...
  • Effectiveness of TMC AI Applications in Case Studies
    Effectiveness of TMC AI Applications in Case Studies
    Yang, H. ;
    Cetin, Mecit
    2022-02-01 | PDF
    Traffic incident detection is a crucial task in traffic management centers (TMCs) that typically manage large highway networks with limited staff. An effective automatic incident-detection approach could benefit TMCs by helping to report abnormal events in a timely and accurate manner and optimize operating resources. During the past decades, resea ...
  • Passenger Flow Modeling and Simulation in Transit Stations
    Passenger Flow Modeling and Simulation in Transit Stations
    Liu, Xiang ;
    Zhu, Yadi
    2022-02-01 | PDF
    Crowd analysis and management is key area of study for transit agencies to maximize operational efficiency and minimize risk. Passenger flow volume, crowd density and walking speed are key features of crowd analytics. This study proposes a generalized Artificial Intelligence (AI)-based crowd analytics model framework for rail transit stations, by a ...
  • Lane Changing of Autonomous Vehicles in Mixed Traffic Environments A Reinforcement Learning Approach
    Lane Changing of Autonomous Vehicles in Mixed Traffic Environments: A Reinforcement Learning Approach
    Jiang, Zhong-Ping ;
    Ozbay, Kaan
    2022-02-01 | PDF
    The purpose of this proposal is to develop innovative reinforcement learning control methods for lane changing of connected and autonomous vehicles (CAVs) in mixed traffic. In the proposed framework, before the CAV changes to the target lane, it needs to predict most likely behavior of surrounding vehicles related to the lane change and then determ ...
  • Railroad Trespass Detection Using Deep LearningBased Computer Vision Research Results
    Railroad Trespass Detection Using Deep Learning-Based Computer Vision [Research Results]
    Jacobini, Francesco Bedini ;
    Ngamdung, Tashi
    2022-02-01 | PDF
    The U.S. Department of Transportation John A. Volpe National Transportation Systems Center (Volpe), under the direction of the Federal Railroad Administration (FRA) Office of Research, Development, and Technology, developed an AI software application for automating the detection of grade crossing violations and trespass activities from static camer ...
  • Development of Cracking Condition Assessment System for Concrete Bridge Decks Using Image Processing Techniques
    Development of Cracking Condition Assessment System for Concrete Bridge Decks Using Image Processing Techniques
    Zhou, Shanglian ;
    Song, Wei
    2022-01-31 | PDF
    Modern society requires a sustainable, robust, and serviceable infrastructure system to promote social welfare and boost economy. To support such an infrastructure system, an efficient health monitoring framework is needed which can promptly detect the presence of defects and perform associated rehabilitation and maintenance. In civil infrastructur ...
  • DeepHyd A Deep LearningBased Artificial Intelligence Approach for the Automated Classification of Hydraulic Structures From LiDAR and Sonar Data
    DeepHyd: A Deep Learning-Based Artificial Intelligence Approach for the Automated Classification of Hydraulic Structures From LiDAR and Sonar Data
    Tang, Wenwu ;
    Chen, Shen-En
    2022-01-30 | PDF
    Monitoring the conditions of hydraulic structures such as bridges and culverts is essential in warranting the safety and sustainability of transportation infrastructure. This is particularly important for North Carolina as more than 8 percent of NC bridges have been found in poor conditions and need immediate maintenance. Lidar and sonar technologi ...
  • A Hybrid Platform for ContextAware V2X Communication
    A Hybrid Platform for Context-Aware V2X Communication
    Hefeida, Mohamed ;
    Mohamed, Umair
    2022-01-01 | PDF
    This report presents a new paradigm for Mobile Edge Learning ("MEL") that enables the implementation of realistic distributed machine learning (DML) tasks on wireless edge nodes while taking into consideration heterogeneous computing and networking environments. A heterogeneity aware (HA) scheme was designed to solve the problem of dynamic task all ...
  • Bias Estimation of Spatiotemporal Traffic Sensor Data with PhysicsInformed Deep Learning Techniques
    Bias Estimation of Spatiotemporal Traffic Sensor Data with Physics-Informed Deep Learning Techniques
    Yang, Han
    2022-01-01 | PDF
    Efficient operations of intelligent transportation systems rely on high-quality traffic data. Infrastructure-based traffic sensors, though providing major data sources for ITS, are subject to data quality issues. Existing studies have attended to identifying malfunctioning sensors or recovering missing data. Nevertheless, critical gaps remain to be ...
  • Identifying Deviations from Normal Driving Behavior
    Identifying Deviations from Normal Driving Behavior
    Hananeh Alambeigi, H ;
    McDonald, Anthony D
    2022-01-01 | PDF
    One of the critical circumstances in automated vehicle driving is transition of control between partially automated vehicles and drivers. One approach to enhancing the design of transition of control is to predict driver behavior during a takeover by analyzing a driver's state before the takeover occurs. Although there is a wealth of existing drive ...
481 - 500 / 613
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